Staff Backend / Product Engineer - FinOps & AI Cost Intelligence Platform
RemoteUnited States
Job Summary
Design and build backend-heavy platform features that productionalize AI-enabled capabilities like anomaly detection and agent-based workflows. Implement AI thoughtfully across the SDLC, from prototyping to deployment, while designing distributed data pipelines that process cloud billing, usage, and telemetry. Construct reliable systems handling backfills and late-arriving data, and establish scalable data models and APIs for customer-facing analytics. Collaborate with Product to turn vision into shipped features, utilizing rigorous evaluation harnesses and rollout strategies to ensure models improve predictably. Success includes shipping 2+ production-ready features and establishing repeatable engineering patterns for AI development within a globally distributed, high-ownership environment.
Required Qualifications
- 8+ years of professional software engineering experience
- deep backend expertise in Python
- Java or C++ as secondary languages
- Experience building and operating data-intensive backend systems or pipelines in production
- Strong understanding of data modelling, reliability, and data processing
- Ability to design scalable systems and take them from concept through production
- Experience with AI driven development to accelerate and drive product development
- Hands-on experience building on AWS
- Demonstrated experience using AI in real production systems
- Comfortable working in ambiguity with product-led direction
- Ability to architect backend services that support asynchronous workflows, event-driven pipelines, and AI agents that operate over time rather than single request/response cycles
- Comfort articulating why certain AI approaches were not used, including trade-offs around latency, explainability, data availability, or long-term maintainability
Desired Qualifications
- Tell a compelling story about a product journey, not just features shipped
- Explain why decisions were made and what trade-offs were considered
- Fail fast, learn quickly, and iterate relentlessly
- Clearly articulate technical roadblocks and collaborate on solutions
- Thrive in a fast-paced, high-ownership environment
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.